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1.
Abstract

The aims of this study were to determine the validity of fat mass of the trunk as a predictor for visceral fat area at the umbilicus level and to develop equations to predict visceral fat mass at the umbilicus level using fat mass of the trunk measured by dual-energy X-ray absorptiometry (DXA) and bioelectrical impedance analysis (BIA). The participants were 121 normal Japanese adults (69 males, 52 females). Another 60 volunteer adults (34 males, 26 females) were recruited for examination of cross-validity. Altogether, 41 adults (15 males, 26 females) in the original group and 19 adults (7 males, 12 females) in the cross-validity group received BIA measurement. We measured fat mass by DXA and the BIA system, which was a single-frequency BIA with 8-point contact electrodes, and visceral fat area by computed tomography. We observed significant correlations for visceral fat area in waist circumference (0.56) and fat mass of the trunk measured by DXA (0.64). There was no significant difference in fat mass of the trunk between the DXA and BIA systems, but the BIA system tended to provide an underestimate compared with DXA. With combined fat mass of the trunk measured by DXA and waist circumference as predictors, visceral fat area was estimated by equation (1) (R = 0.87, R 2 = 0.76, standard error of the estimate = 20.9 cm2). When substituting fat mass of the trunk measured by BIA into equation (1), there was no significant difference in visceral fat area between the reference and predicted values. An equation using fat mass of the trunk measured by BIA (equation 2) was obtained (R = 0.89, R 2 = 0.78, standard error of the estimate = 20.7 cm2), but a systematic error was found for the males. There was cross-validity in both equations. In conclusion, fat mass of the trunk is an effective predictor for the visceral fat area at the umbilicus level. Fat mass of the trunk measured by BIA might be a valid method to predict visceral fat, although further studies with larger samples taking into account the extent and type of obesity are required.  相似文献   

2.
There is a large residual volume (RV) error when assessing percent body fat by means of hydrostatic weighing. It has generally been measured before hydrostatic weighing. However, an individual's maximal exhalations on land and in the water may not be identical. The aims of this study were to compare residual volumes and vital capacities on land and when immersed to the neck in water, and to examine the influence of the measurement error on percent body fat. The participants were 20 healthy Japanese males and 20 healthy Japanese females. To assess the influence of the RV error on percent body fat in both conditions and to evaluate the cross-validity of the prediction equation, another 20 males and 20 females were measured using hydrostatic weighing. Residual volume was measured on land and in the water using a nitrogen wash-out technique based on an open-circuit approach. In water, residual volume was measured with the participant sitting on a chair while the whole body, except the head, was submerged . The trial-to-trial reliabilities of residual volume in both conditions were very good (intraclass correlation coefficient > 0.98). Although residual volume measured under the two conditions did not agree completely, they showed a high correlation (males: 0.880; females: 0.853; P < 0.05). The limits of agreement for residual volumes in both conditions using Bland-Altman plots were -0.430 to 0.508 litres. This range was larger than the trial-to-trial error of residual volume on land (-0.260 to 0.304 litres). Moreover, the relationship between percent body fat computed using residual volume measured in both conditions was very good for both sexes (males: r = 0.902; females: r = 0.869, P < 0.0001), and the errors were approximately -6 to 4% (limits of agreement for percent body fat: -3.4 to 2.2% for males; -6.3 to 4.4% for females). We conclude that if these errors are of no importance, residual volume measured on land can be used when assessing body composition.  相似文献   

3.
Abstract

We previously proposed two predictive equations of visceral fat area applicable in a field setting (Demura & Sato, 2007a Demura, S. and Sato, S. 2007a. Prediction of visceral fat area at the umbilicus level using fat mass of the trunk: The validity of bioelectrical impedance analysis. Journal of Sports Sciences, 25: 823–833. [Taylor & Francis Online], [Web of Science ®] , [Google Scholar], 2007b Demura, S. and Sato, S. 2007b. Prediction of visceral fat area in Japanese adults: Proposal of prediction method applicable in a field setting. European Journal of Clinical Nutrition, 61: 727–735. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]). One uses the fat mass of the trunk measured by bioelectrical impedance as the main predictor (equation 1) and the other uses internal fat mass estimated from several anthropometric variables (equation 2). In this study, we examined the inter- and intra-individual accuracy of estimated values using these equations after 8 weeks of exercise training. Participants were 42 Japanese adults aged 42.7 ± 10.3 years (22 males, 20 females). Visceral fat area, body composition, and blood biochemistry were measured at baseline and after 8 weeks. There were no significant differences in reference visceral fat area measured by computed tomography and visceral fat area predicted by the equations either at baseline or after 8 weeks, and the values were highly consistent (equation 1: baseline R 2 = 0.829, after R 2 = 0.860; equation 2: baseline R 2 = 0.832; after R 2 = 0.850). No significant relationship was observed between the reference and change in visceral fat area for equation 1 (males: r = 0.272, P > 0.05; females: r = 0.428, P > 0.05), but there was a significant relationship for females with equation 2 (males: r = 0.279, P > 0.05; females: r = 0.474, P <0.05). Our findings indicate that these equations have high inter-individual consistency but low intra-individual consistency with the reference and are of limited use for the longitudinal evaluation of visceral fat area.  相似文献   

4.
We aimed to assess the agreement of a commercially available bioelectrical impedance analysis (BIA) device in measuring changes in fat, lean and bone mass over a 10-week lifestyle intervention, with dual energy X-ray absorptiometry (DXA) as reference. A sample of 136 volunteers (18–66 years) underwent a physical activity intervention to enhance lean mass and reduce fat mass. BIA (Tanita BC545) and DXA (Hologic Explorer) measures of whole-body composition were taken at baseline and at the end of the intervention. After an average of 74 ± 18 days intervention, DXA showed significant changes in 2 of 3 outcome variables: reduced fat mass of 0.802 ± 1.092 kg (P < 0.001), increased lean mass of 0.477 ± 0.966 kg (P < 0.001); minor non-significant increase of 0.007 ± 0.041 kg of bone mass (P = 0.052). The respective changes in BIA measures were a significant reduction of 0.486 ± 1.539 kg fat (P < 0.001), but non-significant increases of 0.084 ± 1.201 kg lean mass (P = 0.425), and 0.014 ± 0.091 kg bone (P = 0.074). Significant, but moderately weak, correlations were seen in absolute mass changes between DXA and BIA: 0.511 (fat), 0.362 (lean) and 0.172 (bone). Compared to DXA, BIA demonstrated mediocre agreement to changes in fat mass, but poor agreement to lean mass changes. BIA significantly underestimated the magnitude of changes in fat and lean mass compared to DXA.  相似文献   

5.
The purpose of this study was to compare the body fat per cent (BF%) assessed with a unique handheld electrical impedance myography (EIM) device, along with other popular methods, to dual-energy X-ray absorptiometry (DXA). Participants included 33 males (aged 24.3?±?4.6 years) and 38 females (aged 25.3?±?8.9 years) who completed 2 visits separated by 24–72?h. The assessments included DXA, bioelectrical impedance analysis (BIA), skinfold measures (SKF), and three separate EIM measurements. No significant differences in BF% (P?>?0.05) were found between all EIM assessments when compared against DXA for both males and females for each visit. All methods showed no significant differences in BF% (P?>?0.05) between days within themselves. Across both days, the standard error of the estimate (SEE) for the EIM measurements ranged from 2.66% to 3.15%, the SEE for BIA was 2.80 and 2.85, and for SKF was 2.90 and 2.82. The 95% limits of agreement ranged from ±5.34% to ±6.38% for EIM measurements and were highest for SKF (±7.42% and ±7.47%). The total error for both days was largest for SKF (5.20% and 5.35%) and lowest for the EIM measurements (2.48–3.24%). This investigation supports use of a handheld EIM device as an accurate and reliable method of estimating BF% compared to DXA in young, apparently healthy individuals with BF% in the range of 10–22% for males and 20–32% in females and suggests this EIM device be considered a viable alternative to other established field measurements in this population.  相似文献   

6.
The aims of this study were to assess the reliability and validity of three methods of bioelectrical impedance analysis (based on induction between the hand and foot, between one foot and the other foot and between one hand and the other hand) and the skinfold method, and to construct prediction equations for total body density by examining cross-validity in young Japanese adult males. The participants were 50 Japanese males aged 18-27 years (height 1.72 +/- 0.06 m, body mass 64.9 +/- 9.0 kg; mean +/- s), each of whom was measured twice using each of the four methods. Relative body fat based on underwater weighing was used as the criterion for validity. To construct prediction equations for body density, we used multiple regression analysis, whereby all possible combinations were examined. The reliability of all three bioelectrical impedance methods was high (R = 0.999). Three new prediction equations were constructed for the hand-foot method, foot-foot method and skinfold method. The cross-validity of the equations was guaranteed. The relative body fat calculated using the new equations did not differ from that based on the underwater weighing method.  相似文献   

7.
The ability of bioelectrical impedance analysis and anthropometry to predict fat mass and fat-free mass was compared in a sample of 82 male athletes from a wide variety of sports, using dual-energy X-ray absorptiometry (DXA) as the reference method. The percent fat measured by DXA was 10.9 - 4.9% (mean - s ), and fat mass was predicted with a standard error of the estimate of 1.7 kg for skinfolds and 2.8 kg for bioelectrical impedance analysis (P?0.001). Fat-free mass was predicted with a standard error of the estimate of 1.7 kg for anthropometry and 2.6 kg for bioelectrical impedance analysis (P?0.001). Regression of various individual skinfolds and summed skinfolds, to examine the eff ect of skinfold selection combinations by stepwise regression, produced an optimal fat mass prediction using the thigh and abdominal skinfold sites, and an optimal fat-free mass prediction using the thigh, abdominal and supra-ilium sites. These results suggest that anthropometry off ers a better way of assessing body composition in athletes than bioelectrical impedance analysis. Applying the derived equations to a separate sample of 24 athletes predicted fat and fat-free mass with a total error of 2.3 kg (2.9%) and 2.2 kg (2.7%), respectively. Combining the samples introduced more heterogeneity into the sample (n=106), and the optimal prediction of fat mass used six skinfolds in producing a similar standard error of the estimate (1.7 kg), although this explained a further 4% of the variation in DXA-derived fat. Fat-free mass was predicted best from four skinfolds, although the standard error of the estimate and coefficient of determination were unchanged.  相似文献   

8.
The ability of bioelectrical impedance analysis and anthropometry to predict fat mass and fat-free mass was compared in a sample of 82 male athletes from a wide variety of sports, using dual-energy X-ray absorptiometry (DXA) as the reference method. The percent fat measured by DXA was 10.9+/-4.9% (mean +/- s), and fat mass was predicted with a standard error of the estimate of 1.7 kg for skinfolds and 2.8 kg for bioelectrical impedance analysis (P < 0.001). Fat-free mass was predicted with a standard error of the estimate of 1.7 kg for anthropometry and 2.6 kg for bioelectrical impedance analysis (P < 0.001). Regression of various individual skinfolds and summed skinfolds, to examine the effect of skinfold selection combinations by stepwise regression, produced an optimal fat mass prediction using the thigh and abdominal skinfold sites, and an optimal fat-free mass prediction using the thigh, abdominal and supra-ilium sites. These results suggest that anthropometry offers a better way of assessing body composition in athletes than bioelectrical impedance analysis. Applying the derived equations to a separate sample of 24 athletes predicted fat and fat-free mass with a total error of 2.3 kg (2.9%) and 2.2 kg (2.7%), respectively. Combining the samples introduced more heterogeneity into the sample (n = 106), and the optimal prediction of fat mass used six skinfolds in producing a similar standard error of the estimate (1.7 kg), although this explained a further 4% of the variation in DXA-derived fat. Fat-free mass was predicted best from four skinfolds, although the standard error of the estimate and coefficient of determination were unchanged.  相似文献   

9.
Accurate measurement of head volume is indispensable for precise assessments of body composition determined by hydrostatic weighing without head submersion. The purpose of this study was to establish a prediction equation for head volume measured by the immersion method from multiple regression analysis using head parameters (head circumference, head length, head breadth, neck girth and head thickness) as independent variables. The participants were 106 Japanese young adults (55 males and 51 females) aged 17-27 years. Intra-class correlation coefficients (ICCs) for each head parameter and head volume in males and females were very high (ICC = 0.993-0.999, 0.992-0.998). Head circumference was closely related to head volume measured by the immersion method (r = 0.719, 0.861, P < 0.05), and was the most important parameter for the prediction equation in both sexes. Head breadth was related poorly (r = 0.475, 0.500, P < 0.05) and showed a small individual difference. It was, therefore, excluded from the independent variables. The prediction equation for males was predicted head volume = 122.10X1 + 106.19X3 + 37.16X4 - 89.46X5 - 4754.93, R = 0.909, SEE = 121.75 ml, and that for females was predicted head volume = 213.83X1 + 45.24X3 + 36.85X4 - 74.34X5 - 8912.43, R = 0.913, SEE = 136.26 ml (where X1 = head circumference, X3 = head length, X4 = neck girth, X5 = head thickness, and SEE = standard error of the estimate). The limits of agreement for predicted and measured head volume were -234.5 to 234.1 ml for males, and -261.0 to 261.0 ml for females. In cross-validation groups of both sexes, there were no significant differences between measured head volume and predicted head volume. The correlation coefficients between measured head volume and predicted head volume in males and females were 0.894 and 0.908, respectively. The predicted head volume from prediction equations was considered to have high reliability and validity.  相似文献   

10.
Abstract

Information on the prediction of adult relative fat mass (percent body fat,%BF) using measures from pre-pubertal ages and early childhood is scarce. In the present longitudinal study, we assess the development of different anthropometric indicators of percent body fat during childhood, adolescence, and adulthood in 37½-year-old females stratified for low and high percent body fat. Consequently, we study the predictability of percent body fat based on simple anthropometric measurements during childhood and adolescence.

Anthropometric data from the Belgian longitudinal experimental growth study “LEGS” were used. Beginning in 1969, five yearly cohorts of about 100 individuals each (mean age 6 years) were recruited in public kindergartens. Of the original 515 participants (260 males, 255 females) that were measured annually from age 6 to 18 years, 59 males and 60 females agreed to participate in a follow-up study in 2004. During the follow-up measurements, the participants were invited for a body-composition assessment by bioelectrical impedance analysis (BIA). We stratified the participants into low (%BF-BIA < 35%) and high (%BF-BIA≥35%) relative fat mass samples. Pearson correlations were calculated and used as tracking coefficients. Multiple stepwise linear regression was applied with anthropometric variables at each age separately as predictors for adult percent body fat, expressed as%BF-BIA, %BF-Segal, and %BF-D&W (Durnin & Womersley, 1974).

The results indicate that a single skinfold thickness during adolescence is a better predictor for adult percent body fat than adolescent body mass index. Additionally, our results suggest that this holds during childhood as early as from age 8 onwards. The use of single skinfold measurements as predictors for adult adiposity and obesity is supported by other arguments, including: (1) body mass index as a proxy for overweight does not discriminate between fat mass and fat-free mass, and (2) an excess of adipose tissue is more strongly associated with morbidity than the body mass index.  相似文献   

11.
This study examined a method of predicting body density based on hydrostatic weighing without head submersion (HWwithoutHS). Donnelly and Sintek (1984) developed a method to predict body density based on hydrostatic weight without head submersion. This method predicts the difference (D) between HWwithoutHS and hydrostatic weight with head submersion (HWwithHS) from anthropometric variables (head length and head width), and then calculates body density using D as a correction factor. We developed several prediction equations to estimate D based on head anthropometry and differences between the sexes, and compared their prediction accuracy with Donnelly and Sintek's equation. Thirty-two males and 32 females aged 17-26 years participated in the study. Multiple linear regression analysis was performed to obtain the prediction equations, and the systematic errors of their predictions were assessed by Bland-Altman plots. The best prediction equations obtained were: Males: D(g) = -164.12X1 - 125.81X2 - 111.03X3 + 100.66X4 + 6488.63, where X1 = head length (cm), X2 = head circumference (cm), X3 = head breadth (cm), X4 = head thickness (cm) (R = 0.858, R2 = 0.737, adjusted R2 = 0.687, standard error of the estimate = 224.1); Females: D(g) = -156.03X1 - 14.03X2 - 38.45X3 - 8.87X4 + 7852.45, where X1 = head circumference (cm), X2 = body mass (g), X3 = head length (cm), X4 = height (cm) (R = 0.913, R2 = 0.833, adjusted R2 = 0.808, standard error of the estimate = 137.7). The effective predictors in these prediction equations differed from those of Donnelly and Sintek's equation, and head circumference and head length were included in both equations. The prediction accuracy was improved by statistically selecting effective predictors. Since we did not assess cross-validity, the equations cannot be used to generalize to other populations, and further investigation is required.  相似文献   

12.
The purpose of this study was to assess the accuracy of three recommended anthropometric equations for women and then develop an updated prediction equation using dual energy x-ray absorptiometry (DXA). The percentage of body fat (%BF) by anthropometry was significantly correlated (r = .896-.929; p < .01) with DXA, but each equation underestimated %BF (3.2-5.6 %BF; p < .01). The following DXA criterion (DC) equation was created: %BF= -6.40665 + 0.41946(S3SF) - 0.00126(S3SF)2 + 0.12515(hip) + 0.06473 (age); (S3SF = sum of triceps, suprailiac, thigh; hip = circumference in cm; age = years). The predicted residual sum of squares (PRESS) R2 was high (0.86), and the PRESS standard error of estimate (SEE) was low (2.5 %BF) for our sample of 150 women. The DC equation was further crosschecked on a separate sample of women (n = 25) and again showed excellent agreement. The DC equation appears to be a more accurate estimation of %BF in women.  相似文献   

13.
Abstract

The aim of this study was to compare equations for estimating percentage body fat from skinfold thickness in elite sport climbers by assessing their agreement with percentage body fat measured using dual-energy X-ray absorptiometry (DXA). Skinfold thickness was measured in a convenience sample of 19 elite sport climbers [9 women and 10 men; mean age 31.2 years (s = 5.0) and 28.6 years (s = 3.6), respectively]. Percentage body fat was estimated using 17 different equations, and it was also measured by DXA. A significant inter-methods difference was observed for all equations, except for Durnin's equation in men (inter-methods difference: ?0.57% and ?0.29%; 1.96 s: 5.56 and 5.23 for Siri's and Brozek's equation, respectively) and women (inter-methods difference: ?0.67% and ?1.29% for Siri's and Brozek's equation, respectively), and for Wilmore's equation using Siri's body fat equation in women (inter-methods difference: ?1.86%). In women, the limits of agreement were lower when using Durnin's equation compared with Wilmore's equation (1.96 s: 3.86% and 5.13%, respectively). In conclusion, of the 17 studied equations, Durnin's equation was the most accurate in estimating percentage body fat in both male and female elite climbers. Therefore, Durnin's equation could be used to assess percentage body fat in elite sport climbers if more accurate methods are not available. The generalizability of the results is limited by the fact that the sample was not selected at random.  相似文献   

14.
Abstract

The purpose of this study was to examine the accuracy and reliability of whole-body volume, body density, and percent body fat calculated from body volume without the head (V NH), as assessed by hydrostatic weighing without head submersion and predicted head volume (pV H) based on head parameters, as compared with standard hydrostatic weighing. Participants comprised 29 males and 27 females aged 17–26 years. Head volume was predicted from anthropometric head parameters using a prediction equation. Underwater weights with/without head submersion were measured five times. The reliability of underwater weighing without head submersion was very good (intraclass correlation coefficient: males=0.998, females=0.998) as was that for traditional head submersion. The relationship between the sum of V NH and pV H and the whole-body volume measured by hydrostatic weighing was very high (males=0.998, females=0.999), and their values were very similar with an error range of 300–400 ml. Although percent body fat assessed from the sum of V NH and pV H showed a slight scatter of 2–3% from the identity line of percent body fat assessed by hydrostatic weighing, the relationships for both sexes were very strong (males=0.918, females=0.957). The errors (2 standard deviations) as determined by Bland-Altman plots between the two methods were ?3.2 to 2.6% in males and ?2.3 to 2.8% in females. There was no significant bias in percent body fat estimated by the two methods (hydrostatic weighing with/without head submersion), and the sum of V NH and pV H could validly estimate body composition, regardless of physical size. It is suggested that hydrostatic weighing without head submersion is a valid and convenient alternative technique.  相似文献   

15.
The aim of the present study was to develop and cross-validate anthropometrical prediction equations for segmental lean tissue mass (SLM). One hundred and seventeen young healthy Caucasians (67 men and 50 women; mean age: 31.9 ± 10.0 years; Body Mass Index: 24.3 ± 3.2 kg · m(-2)) were included. Body mass (BM), stretch stature (SS), 14 circumferences (CC), 13 skinfolds (SF) and 4 bone breadths (BB) were used as anthropometric measurements. Segmental lean mass of both arms, trunk and both legs were measured by dual energy X-ray absorptiometry as the criterion method. Three prediction equations for SLM were developed as follows: arms = 40.394(BM) + 169.836(CCarm-tensed) + 399.162(CCwrist) - 85.414(SFtriceps) - 39.790(SFbiceps) - 7289.190, where Adj.R (2) = 0.97, P < 0.001, and standard error of estimate (SEE) = 355 g;trunk = 181.530(BM) + 155.037(SS) + 534.818(CCneck) + 175.638(CCchest) - 88.359(SFchest) - 147.232(SFsupraspinale) - 46522.165, where Adj.R(2) = 0.97, P < 0.001, and SEE = 1077g; and legs = 55.838(BM) + 88.356(SS) + 235.579(CCmid-thigh) + 278.595(CCcalf) + 288.984(CCankle) - 84.954(SFfront-thigh) - 53.009(SFmedial calf) - 28522.241, where Adj.R (2) = 0.96, P < 0.001, and SEE = 724 g. Cross-validation statistics showed no significant differences (P < 0.05) between observed and predicted SLM. Root mean squared errors were smallest for arms (362 g), followed by legs (820 g) and trunk (1477 g). These new prediction equations allow an accurate estimation of segmental lean mass in groups of young adults, but estimation errors of 8 to 14% can occur in certain individuals.  相似文献   

16.
Although it is clear that rowers have a large muscle mass, their distribution of muscle mass and which of the main motions in rowing mediates muscle hypertrophy in each body part are unclear. We examine the relationships between partial motion power in rowing and muscle cross-sectional area of the thigh, lower back, and upper arms. Sixty young rowers (39 males and 21 females) participated in the study. Joint positions and forces were measured by video cameras and rowing ergometer software, respectively. One-dimensional motion analysis was performed to calculate the power of leg drive, trunk swing, and arm pull motions. Muscle cross-sectional areas were measured using magnetic resonance imaging. Multiple regression analyses were carried out to determine the association of different muscle cross-sectional areas with partial motion power. The anterior thigh best explained the power demonstrated by leg drive (r2 = 0.508), the posterior thigh and lower back combined best explained the power demonstrated by the trunk swing (r2 = 0.493), and the elbow extensors best explained the power demonstrated by the arm pull (r2 = 0.195). Other correlations, such as arm muscles with leg drive power (r2 = 0.424) and anterior thigh with trunk swing power (r2 = 0.33 5), were also significant. All muscle cross-sectional areas were associated with rowing performance either through the production of power or by transmitting work. The results imply that rowing motion requires a well-balanced distribution of muscle mass throughout the body.  相似文献   

17.
The purpose of this study was to analyse associations between lean soft tissue (LST), a surrogate of skeletal muscle mass and key fracture-related geometric characteristics of the proximal femur. Moreover, we examined the role that muscle played on the proximal femur geometry in response to physical activity (PA). Participants were 83 young adults. Leg LST (exposure) was assessed by dual energy X-ray absorptiometry (DXA). Proximal femur geometry was derived from a left hip DXA scan. Geometric variables (outcomes) included the femoral neck axis length (FNAL), the femoral neck width (FNW), the neck–shaft angle and FNW|FNAL (an index of robustness). PA was evaluated by accelerometry. Linear regression was used to analyse relationships. Additional exposure variables included body height and mass. In males, leg LST explained 17.4% of variation in FNAL (P < 0.001) and 15% in FNW (P = 0.015). In females, it explained 8.8% of the variance in FNAL (P = 0.020). Associations remained significant in males, but not in females, when vigorous PA was added to the models. These results suggest that public health approaches to promote PA may be particularly important in females since vigorous PA seems to convey advantages in femur geometry and consequently in bone strength.  相似文献   

18.
Accurate measurement of head volume is indispensable for precise assessments of body composition determined by hydrostatic weighing without head submersion. The purpose of this study was to establish a prediction equation for head volume measured by the immersion method from multiple regression analysis using head parameters (head circumference, head length, head breadth, neck girth and head thickness) as independent variables. The participants were 106 Japanese young adults (55 males and 51 females) aged 17?–?27 years. Intra-class correlation coefficients (ICCs) for each head parameter and head volume in males and females were very high (ICC = 0.993?–?0.999, 0.992?–?0.998). Head circumference was closely related to head volume measured by the immersion method (r = 0.719, 0.861, P <?0.05), and was the most important parameter for the prediction equation in both sexes. Head breadth was related poorly (r = 0.475, 0.500, P <?0.05) and showed a small individual difference. It was, therefore, excluded from the independent variables. The prediction equation for males was predicted head volume = 122.10X 1 + 106.19X 3 + 37.16X 4 - 89.46X 5 - 4754.93, R = 0.909, SEE = 121.75?ml, and that for females was predicted head volume = 213.83X 1 + 45.24X 3 + 36.85X 4 - 74.34X 5 - 8912.43, R = 0.913, SEE = 136.26?ml (where X 1 = head circumference, X 3 = head length, X 4 = neck girth, X 5 = head thickness, and SEE = standard error of the estimate). The limits of agreement for predicted and measured head volume were –?234.5 to 234.1?ml for males, and ??261.0 to 261.0?ml for females. In cross-validation groups of both sexes, there were no significant differences between measured head volume and predicted head volume. The correlation coefficients between measured head volume and predicted head volume in males and females were 0.894 and 0.908, respectively. The predicted head volume from prediction equations was considered to have high reliability and validity.  相似文献   

19.
Two research groups recently produced equations for estimation of body volume from dual-energy x-ray absorptiometry (DXA) scans. These body volume estimates can be used for body composition evaluation in modified 4-compartment models. In the present analysis, the reliability of body volume calculations, as well as their usage in 4-compartment models, was explored while employing precise scheduling of assessments and dietary standardization. Forty-eight recreationally active males and females completed two pairs of identical assessments, which included a DXA scan and single-frequency bioelectrical impedance analysis. Each assessment within a pair was separated by 24 hours, during which participants were provided a standardized diet. Body volume and 4-compartment equations were applied to the data, and metrics of reliability and agreement were calculated for body volume and 4-compartment components. While both body volume equations demonstrated excellent reliability individually, substantial disagreement between equations was present when utilized in 4-compartment equations. The magnitude of this disagreement was 4.3 kg for lean mass and fat mass and 6.9% for body fat percentage. At present, the large discrepancies in body composition components when using existing body volume equations preclude their interchangeability and demonstrate the need for continued exploration of the utility of body volume estimates.  相似文献   

20.
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